Noise Source Applications
1. Benchtop noise figure testing.
Perhaps the highest visibility noise application is simply using a calibrated noise source in conjunction with a benchtop test
instrument to measure noise figure of an LNA, mixer or receiver front end.
Measurements can be made with
a dedicated noise figure meter, or by employing the Y-factor method in conjunction with a spectrum analyzer or a power meter with front-end filter. Noise
sources used in this capacity should be accurately calibrated for excess noise ratio (ENR) and have low VSWR.

2. Automatic Test Equipment (ATE).
The proliferation of mixed signal semi-conductor devices has resulted in noise figure measurements to be made directly on the
wafer. Noise sources are mounted in the unit and automatically switched in to make the noise figure measurement. Because the wafer probe and various RF
paths are located between the noise source and the wafer, accurate path loss and reflection coefficient must be compensated. Data is loaded along with the
noise source ENR and reflection coefficients into the ATE control system for very accurate and fast measurements.

3. Built in test for RF receivers and radiometers
Often radar receivers, radiometers and digital radio applications will utilize a built-in noise source to test the health of
the RF receiver. These systems typically switch in the noise source during off times.
Typical measurements
which can be made are noise temperature, sensitivity, gain and frequency response. Because a noise source instantly generates a full band signal flat over
frequency, full frequency response can be measured with minimal down time. Noise sources employed in these live, outdoor applications should have isolators
on the output which serve a dual purpose; to protect the noise source and other circuitry from possible incident power surges from the antenna and to
ensure a low VSWR for lower noise figure measurement uncertainty. Noise sources can be calibrated with the isolator in place for greater accuracy.

4. Eb/No vs BER testing of a modem or digital receiver:
Eb/No literally translates to a ratio of bit energy to noise power in a 1 Hz bandwidth. This is a useful expression for
expressing signal to noise ratio (SNR). BER is simply the bit error rate of digital trans-mission. The lower the Eb/No, the higher the BER. Every digital
radio uses a modulation scheme which will have an ideal Eb/No vs. BER curve. In order to benchmark the actual hardware to the theoretical, a noise signal
is summed with the data modulated test signal setting up a laboratory calibrated Eb/No which is then fed into a bit error rate tester (BERT) to determine
the systems actual curve. Noise sources used in this capacity are typically amplified to test using a wide range of Eb/No ratios.
In practice, wireless communication systems such as CDMA telephony and WiFi wireless LAN, tests are
conducted at RF. For satellite systems, it is typically more practical to test at IF, (injected into the modem) or even at baseband. Overall system
performance can then be extrapolated with an offset constant that can be estimated from the noise figure of the RF front end down-converter often referred
to as the low-noise box (LNB).

5. Dithering circuit.
High-speed A/D converters produce RF spurs caused by quantization errors in the analog to digital conversion process. When
viewed on a spectrum analyzer, these resemble the prongs of a comb jutting up from the noise floor. These spurs can significantly compromise sensitivity.
By injecting noise outside the band of interest, a technique called dithering, the spurs can be
virtually eliminated. Many satellite, wireless communications or surveillance systems have extremely weak signals entering the receiver. These highly
sensitive systems are extremely prone to A/D quantization spurs and are the best candidates for dithering circuits. Historically, dithering circuits have
been a luxury, most systems could not afford. Fortunately today there are small surface mount noise diodes designed for this application offered at much
lower costs suitable for today's high volume commercial circuit-boards.

6. Encryption:
It has been said that an electrical thermal noise source is more random than anything else in nature. By sampling a noise
source voltage at any given snapshot in time one can create a random occurrence to be used as an encryption seed.
Despite all the pseudo-random encryption efforts being designed into wireless and wired
communication and computer networks, the codes can still be cracked. Using a true noise source is perhaps the only practical way to trump the hackers.
Noise sources and modules are now being integrated into highly secure wireless handsets, PC's and network routers and switches.

7. Jamming/Jamming Simulation:
High power amplified noise modules can be used to simulate jammers for RF systems such as missile guidance systems. With the
vast usage of GPS for guidance systems today, significant effort has been made to develop anti-jamming systems for the GPS receiver.
In order to test these systems, one needs to exercise them with simulated jamming signals. Noise
can be used for this in two different ways. The first is to blast white Gaussian noise in the receivers frequency band. The second is to feed noise into
the tuning control of a VCO. For the former, the frequency response is flat and the probability density function is Gaussian. In the latter, the frequency
response is Gaussian and the PDF follows that of a sinusoidal signal.

8. Jitter Testing:
Gaussian noise sources are commonly used to generate random or Gaussian jitter for testing of optoelectronic devices. Feeding
a broadband amplified noise module into phase modulator produces the jitter to mimic real world conditions.
The Optical Internetworking Forum (OIF) has adopted the Common Electrical I/O (CEI) project which
stipulates signaling requirements of these devices including Gaussian Jitter.

9. Baseband Signal Simulation:
Noise sources can be used as a Gaussian modulating signal source to mimic real world conditions such as Rayleigh fading and
other real world simulated models.
By modulating a "clean" signal with Gaussian noise sources, it
is possible to predict how communication devices will react in world conditions but in a repeatable laboratory test.

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